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tmdgitb/pengenalan_pola_shih

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Pengenalan pola

Mengambil byte data dari image.

Cara Menjalankan Aplikasi yang Sudah Dibuild

  1. Buka Command Prompt di folder aplikasi

  2. Jalankan perintah:

     pengenalanpola_shih
    

DaemonApp

Gunakan browser untuk membuka http://localhost:8080/

OBSOLETE: OpenCV

OBSOLETE: No longer required because we use bytedeco's javacpp-presets opencv!

Windows 64-bit

OpenCV for Windows x64 DLL is needed, dan sudah dimasukkan ke git juga biar gampang.

Copy opencv\win_x64\opencv_java*.dll DLL tersebut ke C:\ProgramData\Oracle\Java\javapath

Hendy's internal note: The org.opencv:opencv artifact is published in soluvas-public-thirdparty. You can re-publish (if you update the OpenCV version) to soluvas-thirdparty using:

mvn deploy:deploy-file -DrepositoryId=soluvas-public-thirdparty -Durl=http://nexus.bippo.co.id/nexus/content/repositories/soluvas-public-thirdparty/ -Dfile=opencv/opencv-2411.jar -Dpackaging=jar -DgroupId=org.opencv -DartifactId=opencv -Dversion=2.4.11

Ubuntu 14.04 / Linux Mint 17

  1. Install libopencv2.4-jni (works on Power too):

     sudo aptitude install libopencv2.4-java libopencv2.4-jni
    
  2. Symlink libopencv_java248.so. For x64, while you can put it in /usr/java/packages/lib/amd64 it's still easier and portable to just use /usr/lib. For ppc64el, opencv_java248 will be looked from /opt/ibm/java-ppc64le-80/jre/lib/ppc64le/compressedrefs:/opt/ibm/java-ppc64le-80/jre/lib/ppc64le:/usr/lib

     sudo ln -sv /usr/lib/jni/libopencv_java248.so /usr/lib
    

IntelliJ Run/Console Encoding Troubleshooting

If you get weird characters instead of proper Unicode chaincode "↓↘↓↓↘↓↘↓↘↓↓↘↓↓", set Settings → File Encoding → Project Encoding → IDE Encoding, select UTF-8.

ChainCodeApp

Before Freeman (FCCE):

Processing image file 'AA.jpg' ...
Image mat: rows=96 cols=149 depth=0 type=16
ukuran gambar 96149
Chaincode object #0 at (34, 21): 33333333335455454545545545454554554545545455455454545545545477777777771811811811887777777777777777777766555656556577777777711212112112121121211211211212112112121121211211212
Chaincode subobject : 54554554545545545577777777777711121211211212112
Chaincode object #1 at (103, 21): 33333333335454554545545545454554554545545455454554554545545477777777771181811811887777777777777777777766556556556577777777711212112112121121211211212112112121121121211211212
Chaincode subobject : 54554554545545545577777777777711121211211211212
size chaincode 2
Chaincode char #1 = 33333333335455454545545545454554554545545455455454545545545477777777771811811811887777777777777777777766555656556577777777711212112112121121211211211212112112121121211211212

After Freeman (FCCE):

Processing image file 'AA.jpg' ...
Image mat: rows=96 cols=149 depth=0 type=16
ukuran gambar 96149
Chaincode object #0 at (34, 21): →→→→→→→→→→↓↘↓↓↘↓↘↓↘↓↓↘↓↓↘↓↘↓↘↓↓↘↓↓↘↓↘↓↓↘↓↘↓↓↘↓↓↘↓↘↓↘↓↓↘↓↓↘↓↘←←←←←←←←←←↑↖↑↑↖↑↑↖↑↑↖↖←←←←←←←←←←←←←←←←←←←←↙↙↓↓↓↙↓↙↓↓↙↓←←←←←←←←←↑↑↗↑↗↑↑↗↑↑↗↑↗↑↑↗↑↗↑↑↗↑↑↗↑↑↗↑↗↑↑↗↑↑↗↑↗↑↑↗↑↗↑↑↗↑↑↗↑↗
Chaincode subobject : ↓↘↓↓↘↓↓↘↓↘↓↓↘↓↓↘↓↓←←←←←←←←←←←←↑↑↑↗↑↗↑↑↗↑↑↗↑↗↑↑↗
Chaincode object #1 at (103, 21): →→→→→→→→→→↓↘↓↘↓↓↘↓↘↓↓↘↓↓↘↓↘↓↘↓↓↘↓↓↘↓↘↓↓↘↓↘↓↓↘↓↘↓↓↘↓↓↘↓↘↓↓↘↓↘←←←←←←←←←←↑↑↖↑↖↑↑↖↑↑↖↖←←←←←←←←←←←←←←←←←←←←↙↙↓↓↙↓↓↙↓↓↙↓←←←←←←←←←↑↑↗↑↗↑↑↗↑↑↗↑↗↑↑↗↑↗↑↑↗↑↑↗↑↗↑↑↗↑↑↗↑↗↑↑↗↑↑↗↑↗↑↑↗↑↑↗↑↗
Chaincode subobject : ↓↘↓↓↘↓↓↘↓↘↓↓↘↓↓↘↓↓←←←←←←←←←←←←↑↑↑↗↑↗↑↑↗↑↑↗↑↑↗↑↗
size chaincode 2
Chaincode char #1 = 00000000006766767676676676767667667676676766766767676676676744444444442322322322334444444444444444444455666565665644444444422121221221212212122122122121221221212212122122121

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Membaca byte image, dan dibuat histogram

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